Recent Works

Project data collected from: Reconnecting Asia Project Database: various types of infrastructure projects across the Eurasian supercontinent since 2006. AIDDATA GeoQuery: most projects in Africa. Boston University Global China Dataset: most projects in Asia. NYU Shanghai: projects across the world. Project map:

Abstract The accuracy of snow depth retrieval by remote sensing depends heavily on the characteristics of the snow, and both passive microwave and visible/infrared sensors can contribute to the acquisition of this information. A method integrating these two remotely sensed data sets is presented in this study. Snow depth retrieval is performed using microwave brightness temperature at 19 and… Read more Improved snow depth retrieval by integrating microwave brightness temperature and visible/infrared reflectance

Abstract A new image-registration method is presented by integrating the area-based and feature-based methods. The integrated method is characterized by a novel similarity metric based on spatial and mutual information (SMI), the ant colony optimization for continuous domain (ACO), and a two-phase searching strategy. The SMI-based metric takes into account both spatial relations of detected… Read more Automatic Registration of Multisensor Images Using an Integrated Spatial and Mutual Information (SMI) Metric

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Abstract Heavy precipitation and storm surges often co-occur and compound together to form sudden and severe flooding events. However, we lack comprehensive observational tools with high temporal and spatial resolution to capture these fast-evolving hazards. Remotely sensed images provide extensive spatial coverage, but they may be limited by adverse weather conditions or platform revisiting schedule.… Read more Estimating Daily Inundation Probability Using Remote Sensing, Riverine Flood, and Storm Surge Models: A Case of Hurricane Harvey

ABSTRACT Satellite remote sensing has been widely used to monitor surface water, but its application in observing rapid inundation changes remains challenging. Observations relying on only one sensor could hardly achieve both high temporal and high spatial resolutions. High spatial resolution images are not frequent enough to capture the fast-changing inundation, while high temporal resolution… Read more Automated estimation of daily surface water fraction from MODIS and Landsat images using Gaussian process regression